Journal
INTEGRATIVE AND COMPARATIVE BIOLOGY
Volume 55, Issue 6, Pages 1005-1017Publisher
OXFORD UNIV PRESS INC
DOI: 10.1093/icb/icv084
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Funding
- National Science Foundation [NSF-0744649, IOS-1457162, NSF CNS-0821622, IOS 1457162]
- National Institute of Health [1R01GM097502, R01MH097062]
- National Aeronautics and Space Administration (NASA) [NNX13AJ31G]
- McKnight Brain Research and University of Florida Opportunity Funds
- Division Of Integrative Organismal Systems
- Direct For Biological Sciences [1457162, 1146575] Funding Source: National Science Foundation
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The origins of neural systems and centralized brains are one of the major transitions in evolution. These events might occur more than once over 570-600 million years. The convergent evolution of neural circuits is evident from a diversity of unique adaptive strategies implemented by ctenophores, cnidarians, acoels, molluscs, and basal deuterostomes. But, further integration of biodiversity research and neuroscience is required to decipher critical events leading to development of complex integrative and cognitive functions. Here, we outline reference species and interdisciplinary approaches in reconstructing the evolution of nervous systems. In the omic era, it is now possible to establish fully functional genomics laboratories aboard of oceanic ships and perform sequencing and real-time analyses of data at any oceanic location (named here as Ship-Seq). In doing so, fragile, rare, cryptic, and planktonic organisms, or even entire marine ecosystems, are becoming accessible directly to experimental and physiological analyses by modern analytical tools. Thus, we are now in a position to take full advantages from countless experiments Nature performed for us in the course of 3.5 billion years of biological evolution. Together with progress in computational and comparative genomics, evolutionary neuroscience, proteomic and developmental biology, a new surprising picture is emerging that reveals many ways of how nervous systems evolved. As a result, this symposium provides a unique opportunity to revisit old questions about the origins of biological complexity.
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